sgpp::base::ScalarFunction Class Reference

Abstract base class for scalar-valued functions \(f\colon [0, 1]^d \to \mathbb{R}\) (e.g., objective functions in optimization). More...

#include <ScalarFunction.hpp>

Inheritance diagram for sgpp::base::ScalarFunction:

Public Member Functions
virtual void	clone (std::unique_ptr< ScalarFunction > &clone) const =0
	Pure virtual method for cloning the function.
virtual void	eval (const DataMatrix &x, DataVector &value)
	Convenience method for calculating \(f(\vec{x})\) for multiple \(\vec{x}\).
virtual double	eval (const DataVector &x)=0
	Pure virtual method for calculating \(f(\vec{x})\).
size_t	getNumberOfParameters () const
	ScalarFunction (size_t d)
	Constructor.
virtual	~ScalarFunction ()
	Destructor.

Protected Attributes
size_t	d
	dimension of the domain

Detailed Description

Abstract base class for scalar-valued functions \(f\colon [0, 1]^d \to \mathbb{R}\) (e.g., objective functions in optimization).

Constructor & Destructor Documentation

ScalarFunction()

sgpp::base::ScalarFunction::ScalarFunction ( size_t  d )

inlineexplicit

Constructor.

Parameters

d	dimension of the domain

~ScalarFunction()

virtual sgpp::base::ScalarFunction::~ScalarFunction ( )

inlinevirtual

Destructor.

Member Function Documentation

clone()

virtual void sgpp::base::ScalarFunction::clone ( std::unique_ptr< ScalarFunction > &  clone ) const

pure virtual

Pure virtual method for cloning the function.

It should generate a pointer to the cloned object and it's used for parallel computations (the eval() method might not be thread-safe).

Parameters

[out]

clone

pointer to cloned object

Implemented in sgpp::optimization::ASInterpolantScalarFunction, sgpp::optimization::test_problems::FloudasObjective, sgpp::optimization::test_problems::G03Objective, sgpp::optimization::test_problems::G04Objective, sgpp::optimization::test_problems::G04SquaredObjective, sgpp::optimization::test_problems::G05Objective, sgpp::optimization::test_problems::G06Objective, sgpp::optimization::test_problems::G08Objective, sgpp::optimization::test_problems::G09Objective, sgpp::optimization::test_problems::G10Objective, sgpp::optimization::test_problems::G11Objective, sgpp::optimization::test_problems::G12Objective, sgpp::optimization::test_problems::G13Objective, sgpp::optimization::test_problems::SimionescuObjective, sgpp::optimization::test_problems::SolandObjective, sgpp::optimization::test_problems::AbsoluteValueObjective, sgpp::optimization::test_problems::AckleyObjective, sgpp::optimization::test_problems::Alpine02Objective, sgpp::optimization::test_problems::BealeObjective, sgpp::optimization::test_problems::Branin01Objective, sgpp::optimization::test_problems::Branin02Objective, sgpp::optimization::test_problems::BubbleWrapObjective, sgpp::optimization::test_problems::EasomYangObjective, sgpp::optimization::test_problems::EggholderObjective, sgpp::optimization::test_problems::GoldsteinPriceObjective, sgpp::optimization::test_problems::GriewankObjective, sgpp::optimization::test_problems::Hartman3Objective, sgpp::optimization::test_problems::Hartman6Objective, sgpp::optimization::test_problems::HimmelblauObjective, sgpp::optimization::test_problems::HoelderTableObjective, sgpp::optimization::test_problems::IncreasingPowerObjective, sgpp::optimization::test_problems::MichalewiczObjective, sgpp::optimization::test_problems::MladineoObjective, sgpp::optimization::test_problems::PermObjective, sgpp::optimization::test_problems::RastriginObjective, sgpp::optimization::test_problems::RosenbrockObjective, sgpp::optimization::test_problems::Schwefel06Objective, sgpp::optimization::test_problems::Schwefel22Objective, sgpp::optimization::test_problems::Schwefel26Objective, sgpp::optimization::test_problems::SHCBObjective, sgpp::optimization::test_problems::SphereObjective, sgpp::optimization::test_problems::TremblingParabolaObjective, sgpp::base::ComponentScalarFunction, sgpp::base::InterpolantScalarFunction, sgpp::base::ScaledScalarFunction, sgpp::base::WrapperScalarFunction, and sgpp::datadriven::KDEMaximumLikelihoodCrossValidation.

Referenced by sgpp::optimization::IterativeGridGenerator::evalFunction(), and sgpp::optimization::optimizer::DifferentialEvolution::optimize().

eval() [1/2]

virtual void sgpp::base::ScalarFunction::eval ( const DataMatrix &  x, DataVector &  value  )

inlinevirtual

Convenience method for calculating \(f(\vec{x})\) for multiple \(\vec{x}\).

Parameters

	x	matrix \(\vec{x} \in [0, 1]^{N \times d}\) of evaluation points (row-wise)
[out]	value	\((f(\vec{x}_k))_k\) where \(\vec{x}_k\) is the \(k\)-th row of \(x\)

References d, eval(), sgpp::base::DataMatrix::getNrows(), and sgpp::base::DataMatrix::getRow().

Referenced by python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis::estimateDensity().

eval() [2/2]

virtual double sgpp::base::ScalarFunction::eval ( const DataVector &  x )

pure virtual

Pure virtual method for calculating \(f(\vec{x})\).

Parameters

x	evaluation point \(\vec{x} \in [0, 1]^d\)

Returns

\(f(\vec{x})\)

Implemented in sgpp::optimization::ASInterpolantScalarFunction, sgpp::optimization::test_problems::TestScalarFunction, sgpp::base::ComponentScalarFunction, sgpp::base::InterpolantScalarFunction, sgpp::base::ScaledScalarFunction, sgpp::base::WrapperScalarFunction, and sgpp::datadriven::KDEMaximumLikelihoodCrossValidation.

Referenced by sgpp::datadriven::OperationMakePositiveInterpolateFunction::computeHierarchicalCoefficients(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis::estimateDensity(), eval(), sgpp::base::ComponentScalarFunction::eval(), sgpp::optimization::IterativeGridGenerator::evalFunction(), sgpp::optimization::IterativeGridGeneratorSOO::generate(), and sgpp::optimization::optimizer::DifferentialEvolution::optimize().

getNumberOfParameters()

size_t sgpp::base::ScalarFunction::getNumberOfParameters ( ) const

inline

Returns

dimension \(d\) of the domain

References d.

Referenced by sgpp::optimization::IterativeGridGenerator::evalFunction(), sgpp::optimization::IterativeGridGeneratorFuzzyRitterNovak::generate(), sgpp::optimization::IterativeGridGeneratorRitterNovak::generate(), sgpp::optimization::IterativeGridGeneratorSOO::generate(), and sgpp::optimization::IterativeGridGeneratorLinearSurplus::IterativeGridGeneratorLinearSurplus().

Member Data Documentation

d

size_t sgpp::base::ScalarFunction::d

protected

dimension of the domain

Referenced by sgpp::base::WrapperScalarFunction::clone(), sgpp::optimization::test_problems::TestScalarFunction::eval(), eval(), sgpp::base::InterpolantScalarFunction::eval(), sgpp::base::ScaledScalarFunction::eval(), sgpp::optimization::test_problems::G03Objective::evalUndisplaced(), sgpp::optimization::test_problems::AbsoluteValueObjective::evalUndisplaced(), sgpp::optimization::test_problems::AckleyObjective::evalUndisplaced(), sgpp::optimization::test_problems::Alpine02Objective::evalUndisplaced(), sgpp::optimization::test_problems::BubbleWrapObjective::evalUndisplaced(), sgpp::optimization::test_problems::EasomYangObjective::evalUndisplaced(), sgpp::optimization::test_problems::GriewankObjective::evalUndisplaced(), sgpp::optimization::test_problems::IncreasingPowerObjective::evalUndisplaced(), sgpp::optimization::test_problems::PermObjective::evalUndisplaced(), sgpp::optimization::test_problems::RastriginObjective::evalUndisplaced(), sgpp::optimization::test_problems::RosenbrockObjective::evalUndisplaced(), sgpp::optimization::test_problems::Schwefel22Objective::evalUndisplaced(), sgpp::optimization::test_problems::Schwefel26Objective::evalUndisplaced(), sgpp::optimization::test_problems::SphereObjective::evalUndisplaced(), sgpp::optimization::test_problems::TremblingParabolaObjective::evalUndisplaced(), and getNumberOfParameters().

---

The documentation for this class was generated from the following file:

• base/src/sgpp/base/function/scalar/ScalarFunction.hpp